PostHog MCP Server
Official PostHog MCP Server for product analytics, feature flags, experiments, and more.
A statistical analyst in your AI chat: bring data and a question, get a citable, re-runnable report.
选择你使用的 AI 应用,然后复制设置。
通过 4/4 项检查 · 你的提问会经过开发者的服务器(api.mcpanalytics.ai) · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude · 约 5 分钟
需要 MCP Analytics 的密钥(在开发者网站创建) · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加
CustomizeConnectors
把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue
MCP Analyticshttps://api.mcpanalytics.ai/mcp/api-key在 Request headers 下添加这个名称和值
X-API-Key<在这里粘贴你的密钥>只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 Claude 检测到的登录设置页点击 Continue · Authentication 按作者说明选择(Sign in now、Sign in when needed 或 No sign in),然后点击 Add
+ConnectorsMCP Analytics
用 MCP Analytics 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 MCP Analytics,或回答中出现 MCP Analytics 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 MCP Analytics
MCP Analytics 连接时需要你自己的密钥,但 OpenAI 帮助页面只说明了 OAuth 登录,没有我们能核实的填密钥方式
A · 使用能连接 MCP Analytics 的应用
B · 营销与社交媒体 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
可连接 Claude Code · 约 5 分钟
需要 MCP Analytics 的密钥(在开发者网站创建)
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --transport http --scope user analytics https://api.mcpanalytics.ai/mcp/api-key --header 'X-API-Key: your-value'按 Enter 前,把“your-value”改成你的密钥
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
应能看到 MCP Analytics 在列表中并显示已连接
用 MCP Analytics 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 MCP Analytics,或回答中出现 MCP Analytics 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor · 约 5 分钟
需要 MCP Analytics 的密钥(在开发者网站创建)
在 MCP Analytics 的设置中,X-API-Key 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
用 MCP Analytics 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 MCP Analytics,或回答中出现 MCP Analytics 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code · 约 5 分钟
需要 MCP Analytics 的密钥(在开发者网站创建)
在 MCP Analytics 的设置中,X-API-Key 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
用 MCP Analytics 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 MCP Analytics,或回答中出现 MCP Analytics 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看
通过网页连接的应用使用的地址
https://api.mcpanalytics.ai/mcp/api-keyJSON 设置在下方“开发者专用”中
Claude Code
claude mcp add --transport http --scope user analytics https://api.mcpanalytics.ai/mcp/api-key --header 'X-API-Key: your-value'Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"analytics": {
"url": "https://api.mcpanalytics.ai/mcp/api-key",
"headers": {
"X-API-Key": "your-value"
}
}
}
}VS Code (mcp.json)
{
"servers": {
"analytics": {
"type": "http",
"url": "https://api.mcpanalytics.ai/mcp/api-key",
"headers": {
"X-API-Key": "your-value"
}
}
}
}说明仍为英文原文。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
通过互联网连接,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
工具名称和描述与服务器在 2026年11月13日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
account_linkDirect link to the right account page for anything not doable in chat: billing, browser upload, report management. Hand the user the link and guide them.
aboutPlatform documentation and info: how it works (Answer, Analytics, Custom Analytics), usage.
agent_advisorAI help desk: which analysis fits your question, interpreting results, fixing errors. Multi-turn.
datasets_uploadGet your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for path_resolver; omit it to get an upload link for a file only the user can reach. Add replace_ref (uuid://ID:KEY) with data to REFRESH an existing dataset in
datasets_listList and search your uploaded datasets, with fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference (the `usage` field) for use as dataset_ref in path_resolver and path_tool_run. The id alone ('uuid://dsv2_...') also works for your own datasets an
discover_toolsBrowse the analyses you can run: the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'own' or 'standard_library'). Plain-language match; no query lists everything, your own first. Nothing fits? Commission it with path_resolver.
tools_schemaGet an analysis's parameter schema. ALWAYS call before path_tool_run.
review_estimateThe estimate as you review it WITH the user: the question as understood, the estimated answer (sample, marked), every place and its question, the page link, a review checklist. Before path_bespoke.
adjust_estimateApply the user's layout wishes to the estimate's page through the layout agent; a new named arrangement, nothing overwritten, no number changes.
find_precedentBefore estimating: how did we answer this objective before, on this data or any data? Prior packages and library runs with their tools, mappings, bespoke module names, method and verdicts. Platform-wide, read-only.
check_tool_fitBefore naming a library tool: does it fit THIS dataset for THIS question? Column mapping, missing required inputs, method-fit verdict, the places it delivers. Read-only.
package_statusRead an analytics package back: status, every run under it, the report link once delivered.
my_objectsList and search the objects you own across every question: the curated charts, tables and figures of each delivered package, grouped by objective.
build_statusCheck a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, report link when delivered.
ask_libraryAsk a question across all your delivered analyses: a synthesized answer with citations back to specific reports.
reports_listYour report library: every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.
warehouseQuery your org's data warehouse free: browse the catalog (tables with column roles + computed metrics), semantically find data, plain-language ask, or named templates. Requires warehouse enablement (business plans).
schedulesStanding re-runs of analyses you own: action='create' (weekly/monthly against a re-runnable data reference, connector:// or an https:// link; report emailed after each run), 'list', or 'cancel'.
reports_viewGet a shareable browser link for a report, viewable without authentication.
report_cardsBrowse a delivered report's individual cards (charts, tables, insights) inline in chat.
path_resolverWhich path a question about data should take (reuse, rerun, answer, tool_run, estimate, bespoke, ask or none), with the reason, every path's score and time, and the ready input for the path it picks. Executes nothing and charges nothing.
path_reuseHand back the report already delivered for this question on this data. Time: as path_resolver quotes.
path_rerunRun a delivered analysis again, on its own dataset or a new one: the same tools and mappings, no rebuild. package_id may also be the person's own report link (a /rpt/ link or its rpt_ token) or estimate id (est_); it reruns their newest delivered package for it. Time: as path_res
path_answerA read of the data (a total, an average, a count, the top group), computed on every row, in this response. When the question is not a read it says so and names the next step. Time: as path_resolver quotes. No key yet? Call it with objective and data (a small table, up to 200 rows
path_tool_runRun one or more tested library tools on this dataset, with charts and a written report. No custom build. Time: as path_resolver quotes.
path_estimateA rough answer over a sample and the layout of the full report, for the person to confirm before anything is ordered. Time: as path_resolver quotes.
path_bespokeOrder a custom analysis built for this data from a confirmed estimate, optionally with library tools alongside. Needs the person's yes and an idempotency key; a retry returns the first order. Time: as path_resolver quotes.
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月14日
注册名称已通过域名 mcpanalytics.ai 验证(注册中心会核实域名所有权)
代码最后更新于18天前
不适用:由 mcpanalytics.ai 的所有者自己运行的云端服务器,你不会运行仓库里的代码
在 479 毫秒内响应(HTTP 200)
无需登录
已读取 27 个工具描述,未发现针对 AI 的隐藏指令
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 4 项适用的基础检查中通过了 4 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:X-API-Key
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于18天前,最新版本(1.0.8)于30天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于接受远程 MCP 的应用,例如网页版 ChatGPT(Business 及以上为完整 MCP;Pro 为只读)。
同一分类中有:PostHog MCP Server, Openshorts, Google Ads + Meta Ads + SEO/GEO MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Official PostHog MCP Server for product analytics, feature flags, experiments, and more.
Turn long videos into viral vertical shorts and publish them to TikTok, Instagram and YouTube.
Google Ads, Meta Ads, Google Analytics (GA4) & Search Console MCP server by Ryze AI
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
A statistical analyst in your AI chat. Bring a dataset and a question, get back a citable, re-runnable report with its method named.
MCP Analytics is a Model Context Protocol server that answers business and statistical questions about your data, as deep as each question needs:
Intelligent routing picks the depth: you describe the question, and the server says which path answers it and why. Analytics is repeatable: same data, same numbers. Every report names its method and the code that ran it, and runs again on new data.
It is for business and statistical questions about data, not a general-purpose assistant.
Website: mcpanalytics.ai · Free tools you can try in the browser: mcpanalytics.ai/free
Endpoint: https://api.mcpanalytics.ai/mcp/api-key (Streamable HTTP, JSON-RPC)
Authentication: an API key in the X-API-Key header. Create an account at mcpanalytics.ai and copy your key from your account settings.
{
"mcpServers": { "mcpanalytics": { "url": "https://api.mcpanalytics.ai/mcp/api-key", "headers": { "X-API-Key": "mcp_your_key_here" } } } }
Claude Code:
claude mcp add --transport http mcpanalytics https://api.mcpanalytics.ai/mcp/api-key --header "X-API-Key: mcp_your_key_here"
Browse before you sign up. Without a key the server answers in discovery mode: you can connect and list the tools, but not run anything.
curl -X POST https://api.mcpanalytics.ai/mcp/api-key \
-H 'Content-Type: application/json' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'
Ask your AI assistant a question about your data, for example:
The first call is the resolver: it reads your question and your data, executes nothing and charges nothing, and names the path that answers it (an answer, a library analysis, or a custom build) with the reason. Then it runs that path.
Your uploaded data is used only to answer your questions. See the privacy policy for what we keep and for how long. Security issues: see SECURITY.md.
See LICENSE.